Working on projects across multiple DS disciplines (Tabular datasets, Vision, NLP, Bayesian modeling, etc..).
Apply complex analytical techniques to derive actionable insights.
Converting business needs into working data science projects (Identifying problems and providing solutions from ideation to deployment).
Conducting research and implementing new initiatives.
Working closely with our product, analysis, data and development departments.
Designing and Creating machine learning and DS pipelines used to ease, enhance and automate analysis tasks.
Optimizing and improving existing ML/DL models and pipelines.
Working with big data (BigQuery, SQL).
Roles & Responsibilities:
Identify valuable data sources and automate collection processes.
Undertake the preprocessing of structured and unstructured data.
Analyze large amounts of information to discover trends and patterns.
Build predictive models and machine-learning algorithms.
Propose solutions and strategies for business challenges.
Requirements:
M.Sc / PhD in Computer Science/Mathematics/Statistics/Engineering or related fields.
4+ years of experience of work as a data scientist.
Working on big data projects and environments.
5+ years of experience with python and data science related frameworks and packages (Jupyter, Pandas, Numpy, Scipy, ScikitLearn, Plotly).
Experience with Deep Learning (Pytorch / Tensorflow) within the following disciplines: NLP / Vision / Tabular Data / Time Series Forecasting.
Strong statistical, analytical & problem solving skills.
Hands on SQL skills, ability to understand, write and maintain complex queries.
Team player with strong communication skills.
Strong knowledge of software-engineering principles such as modularity, automated testing, and documentation.
Fluent in english.
Advantages:
Working in research teams.
Experience of reading and reproducing academic papers.
Experience of conducting experiments and optimizing models.
Experience with Google Cloud Platform (BigQuery, CloudRun, CloudFunctions, VertexAI)
Experience with Linux environment and shell scripting.
Domain experience of game analytics (LTV, UA, Creative Analysis, Time Series Analysis).
Experience with leading end-to-end projects.
Required Skills:
Coding.
Communication skills.
self learner.
Methodological.
Deep Learning.
